Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method, the method comprising: delivering a content to a user device; receiving a new pattern, wherein the new pattern is a function of a user facial expression captured by an image sensor on the user device and the new pattern is aligned, in time, with the content, wherein the user device is authenticated to a user; retrieving generic patterns and linked generic values from a pattern store connected to the network, wherein the generic patterns have been captured digitally from a plurality of generic users, and/or user patterns and linked user values from a user profile data store connected to the network, wherein the user patterns have been captured digitally and are linked to the user of the user device; comparing the new pattern with the generic patterns and/or the user patterns to identify one of the generic patterns and/or the user patterns that matches the new pattern; determining a new value from a generic value and/or a user value linked to the one of the generic patterns and/or the user patterns that matches the new pattern as a result of the comparison; linking the new pattern with the new value; adding the new pattern, linked to the new value, to the user profile data store; determining a workflow from a plurality of workflows identified by the new value; initiating the workflow, wherein the determined workflow includes delivering a different content to the user device; and delivering the different content to the user device.
This invention relates to personalized content delivery and user interaction systems, specifically addressing the problem of dynamically adapting content based on real-time user emotional state. The method involves delivering content to a user's device. The device captures a user's facial expression using its image sensor, generating a new pattern that is synchronized with the delivered content. This new pattern is then compared against a database of generic patterns (derived from multiple users) and/or user-specific patterns stored in a user profile. These patterns are associated with linked values. A match between the new facial expression pattern and a stored pattern (generic or user-specific) is identified. Based on this match, a new value is determined from the linked value associated with the matched pattern. This new pattern and its corresponding new value are then stored in the user's profile. The determined new value is used to select a specific workflow from a predefined set of workflows. This selected workflow dictates the delivery of different content to the user device. Therefore, the system dynamically changes the content presented to the user based on their real-time facial expressions, creating a personalized and responsive user experience.
2. The method of claim 1 , wherein the different content includes a music content, a video content, a game content, or an advertising content.
This invention relates to a method for delivering and managing different types of digital content, such as music, video, game, or advertising content, to a user device. The method addresses the challenge of efficiently distributing diverse content types while ensuring seamless user interaction and optimal performance. The system involves a content server that stores and categorizes various content types, each with distinct characteristics and delivery requirements. The method dynamically selects and transmits the appropriate content to a user device based on factors such as user preferences, device capabilities, and network conditions. For music content, the method ensures high-quality audio streaming with minimal latency. For video content, it optimizes resolution and bitrate to match the device's display and network speed. For game content, it prioritizes real-time data synchronization and low-latency interactions. For advertising content, it integrates targeted ads without disrupting the user experience. The method also includes monitoring user engagement and adjusting content delivery in real time to enhance satisfaction. By supporting multiple content types within a unified framework, the invention provides a flexible and efficient solution for digital content distribution.
3. The method of claim 1 , wherein the content is a first lesson and the different content is a different lesson.
This invention relates to educational systems that adaptively present content to users based on their performance. The problem addressed is the inefficiency of traditional linear learning methods, which do not account for individual differences in comprehension or engagement. The invention provides a method for dynamically selecting and presenting educational content to a user, where the content is tailored to the user's needs and progress. The method involves monitoring the user's interaction with a first lesson, such as tracking their responses, time spent, or accuracy. Based on this data, the system determines whether the user requires additional reinforcement or is ready to advance. If reinforcement is needed, the system presents the same or similar content in a modified format. If the user is ready to progress, the system presents a different lesson that builds upon the first. The selection of the next lesson is based on predefined criteria, such as difficulty level, topic relevance, or skill prerequisites. The system may also adjust the presentation of content, such as changing the instructional approach, providing additional examples, or offering interactive exercises. The goal is to optimize learning efficiency by ensuring the user receives the most appropriate content at the right time. This adaptive approach helps prevent frustration from overly difficult material or disengagement from material that is too easy. The invention is applicable to various educational settings, including online courses, tutoring systems, and corporate training programs.
4. The method of claim 1 , wherein the content is a lesson and the different content is a message alerting the user device to pause content delivery for a specified amount of time.
This invention relates to a system for managing content delivery to user devices, particularly in educational or instructional contexts. The problem addressed is ensuring users receive timely and relevant interruptions or alerts during content consumption, such as lessons, without disrupting the overall learning experience. The system involves detecting when a user device is engaged with a lesson and then delivering a different type of content—a message alerting the user to pause the lesson for a specified duration. This pause message can be triggered based on predefined conditions, such as time intervals, user behavior, or external events. The pause duration is configurable, allowing flexibility in how long the interruption lasts before resuming the original content. The system ensures that the pause message is distinct from the lesson content, making it clear to the user that an interruption is occurring. This helps maintain user engagement by providing structured breaks or important notifications without causing confusion. The method also supports resuming the lesson seamlessly after the pause period ends, ensuring continuity in the learning process. This approach is useful in scenarios where users need periodic reminders, breaks, or updates without manually pausing the content themselves. It enhances user experience by automating interruptions in a controlled manner, improving focus and retention.
5. The method of claim 1 , wherein the content is a lesson and the different content is a message alerting the user device to respond to one or more questions pertaining to the lesson.
This invention relates to educational systems that enhance user engagement by integrating interactive content with alerts. The system delivers a lesson to a user device and subsequently sends a message prompting the user to respond to one or more questions related to the lesson. The questions are designed to reinforce learning and assess comprehension. The system may track user responses to evaluate performance and provide feedback. The method ensures that users actively engage with the material, improving retention and understanding. The alerts can be customized based on user behavior, such as sending reminders if responses are delayed or providing additional resources if answers are incorrect. The system may also adapt the difficulty of questions based on prior responses, tailoring the learning experience to individual needs. This approach combines structured educational content with real-time interaction, making learning more dynamic and effective. The invention is particularly useful in online education platforms, corporate training programs, and self-paced learning environments where user engagement is critical.
6. The method of claim 1 , wherein the content is a textual lesson and the different content is a multi-media expression of the textual lesson.
This invention relates to educational content delivery systems, specifically methods for enhancing learning by presenting the same educational material in multiple formats. The problem addressed is the ineffectiveness of single-format instruction, which may not accommodate diverse learning styles or engagement levels. The solution involves providing a textual lesson alongside a multimedia expression of the same lesson, such as audio, video, or interactive elements. This dual-format approach ensures that learners can absorb information through their preferred medium, improving comprehension and retention. The multimedia expression may include visual aids, animations, or interactive simulations that reinforce the textual content. The system dynamically selects or generates these alternative formats based on user preferences, learning progress, or contextual factors like device capabilities. This adaptive delivery ensures accessibility and engagement across different user scenarios, such as mobile devices or varying network conditions. The invention aims to optimize learning outcomes by leveraging multimodal content delivery, catering to both auditory and visual learners while maintaining consistency in educational material.
7. The method of claim 1 , wherein the content is an assessment and the different content is a message alerting the user to respond, using the user device, to the assessment.
This invention relates to a system for managing user interactions with digital content, particularly assessments and alerts. The system detects when a user engages with an assessment, such as a survey or quiz, and automatically generates a message prompting the user to respond. The message is delivered to the user's device, ensuring timely follow-up. The system may also track user responses and adjust subsequent interactions based on engagement patterns. This approach improves response rates by reducing friction in the assessment process, ensuring users are notified when their input is required. The system may integrate with various applications, including productivity tools, educational platforms, and customer feedback systems, to streamline workflows and enhance user participation. The invention addresses the challenge of low engagement in digital assessments by automating reminders and simplifying the response process.
8. A system for correlating detected patterns with delivered content to improve the reception of the delivered content, the system comprising: a network; a user device, connected to the network, including an image sensor, and wherein the user device is authenticated to a user; and a pattern engine connected to the network that: delivers a content to the user device, receives a pattern, wherein the pattern is a function of a user facial expression captured by the image sensor and the pattern aligns, in time, with the content; retrieves: a plurality of generic patterns linked to a plurality of generic values from a pattern store connected to the network, wherein the plurality of generic patterns are digitally captured, and/or a plurality of user patterns linked to a plurality of user values from a user profile data store connected to the network, wherein the plurality of user patterns are linked with the user of the user device and are digitally captured; compares the pattern with the plurality of generic patterns and/or the plurality of user patterns to identify one of the plurality of generic patterns and/or the plurality of user patterns that matches the pattern; determines a pattern value from a generic value and/or a user value linked to the one of the plurality of generic patterns and/or the plurality of user patterns that matches the pattern as a result of the comparison; sends the pattern value to a content manager; links the pattern with the pattern value; and a data server that: adds the pattern linked to the pattern value to the user profile data store; and wherein the content manager is connected to the network, and the content manager: receives the pattern value; determines a workflow from a plurality of workflows identified by the pattern value, initiates the workflow, wherein one of the plurality of workflows includes delivering a different content to the user device, and delivers the different content to the user device.
A system improves content delivery by correlating user reactions with presented content. The system includes a network, a user device with an image sensor, and a pattern engine. The user device is authenticated to a specific user. The pattern engine delivers content to the user device and receives a pattern derived from the user's facial expression captured by the image sensor, where the pattern is time-aligned with the content. The engine retrieves generic patterns linked to generic values from a pattern store and user-specific patterns linked to user values from a user profile data store. These patterns are digitally captured. The engine compares the received pattern with the stored patterns to identify matches, then determines a pattern value from the linked generic or user values of the matching pattern. This value is sent to a content manager, which selects a workflow based on the pattern value. The workflow may include delivering different content to the user device. The system also includes a data server that adds the new pattern-value pair to the user profile data store for future reference. This approach dynamically adjusts content delivery based on real-time user reactions, improving engagement and personalization.
9. The system for correlating detected patterns with delivered content to improve the reception of the delivered content of claim 8 , wherein the different content includes a music content, a video content, a game content, or an advertising content.
A system correlates detected patterns with delivered content to improve content reception. The system identifies patterns in user behavior, environmental conditions, or device states, then adjusts the delivery of content—such as music, video, game, or advertising—to enhance user engagement or satisfaction. The system may analyze factors like user interaction history, time of day, location, or device performance to tailor content delivery dynamically. For example, it might prioritize high-quality video streaming when network conditions are optimal or adjust music playback based on detected ambient noise levels. The system can also track user responses to different content types and refine delivery strategies over time. By aligning content with contextual patterns, the system aims to optimize user experience, reduce interruptions, and increase content effectiveness. The technology is applicable in media streaming, digital advertising, and interactive entertainment, where adapting content delivery to real-time conditions enhances user retention and satisfaction.
10. The system for correlating detected patterns with delivered content to improve the reception of the delivered content of claim 8 , wherein the content is a first lesson and the different content is a second lesson.
A system correlates detected patterns in user behavior with delivered educational content to improve learning outcomes. The system identifies patterns in how users interact with a first lesson, such as engagement levels, time spent, or performance metrics. It then uses these patterns to select or modify a second lesson to enhance comprehension or retention. The system may adjust the difficulty, format, or sequence of the second lesson based on the detected patterns from the first lesson. For example, if a user struggles with a concept in the first lesson, the system may provide additional practice or alternative explanations in the second lesson. The system may also track progress over multiple lessons to refine content delivery dynamically. This approach ensures personalized learning by adapting content to individual needs, improving the effectiveness of educational materials. The system operates in real-time or near-real-time to provide timely adjustments, enhancing the overall learning experience.
11. The system for correlating detected patterns with delivered content to improve the reception of the delivered content of claim 8 , wherein the content is a lesson and the different content is a message alerting the user device to pause content delivery for a specified amount of time.
A system correlates detected user behavior patterns with delivered educational content to enhance learning effectiveness. The system monitors user interactions with a lesson, such as engagement levels, comprehension metrics, or attention span, to identify patterns that may indicate suboptimal learning conditions. Based on these patterns, the system generates and delivers a message to the user device instructing it to pause content delivery for a predefined duration. This pause allows the user to recover focus, process information, or address distractions before resuming the lesson. The system may also adjust subsequent content delivery parameters, such as pacing or difficulty, to better align with the user's current state. The goal is to dynamically optimize the learning experience by preventing information overload or disengagement, thereby improving knowledge retention and comprehension. The system may integrate with adaptive learning platforms, educational software, or digital tutoring tools to provide real-time feedback and content adjustments.
12. The system for correlating detected patterns with delivered content to improve the reception of the delivered content of claim 8 , wherein the content is a lesson and the different content is a message alerting the user device to respond to one or more questions pertaining to the lesson.
This invention relates to an educational system that improves content reception by correlating detected user patterns with delivered lessons and adaptive feedback. The system monitors user interactions with educational content, such as lessons, to identify engagement patterns. Based on these patterns, the system generates and delivers targeted message alerts prompting the user to respond to questions related to the lesson. The alerts are designed to reinforce learning by encouraging active participation and assessing comprehension. The system dynamically adjusts the frequency, timing, or content of these alerts based on the user's response patterns, ensuring personalized and effective learning reinforcement. By analyzing user behavior and adapting the delivery of follow-up questions, the system enhances retention and understanding of the educational material. The approach leverages real-time feedback to optimize the learning experience, making it more interactive and responsive to individual needs. This method ensures that users engage more deeply with the content, leading to improved learning outcomes.
13. The system for correlating detected patterns with delivered content to improve the reception of the delivered content of claim 8 , wherein the content is a textual lesson and the different content is a multi-media expression of the textual lesson.
A system correlates detected patterns in user interactions with delivered content to improve content reception. The system identifies patterns in how users engage with a textual lesson, such as reading speed, comprehension metrics, or navigation behavior. Based on these patterns, the system dynamically adjusts the content delivery by replacing or supplementing the textual lesson with a multimedia expression of the same lesson. The multimedia expression may include video, audio, animations, or interactive elements designed to enhance understanding and retention. The system analyzes user responses to the adjusted content to further refine future content delivery. This approach ensures that content is tailored to individual learning preferences and cognitive engagement levels, improving overall reception and effectiveness. The system may also track long-term retention and adapt content formats over time to maintain optimal learning outcomes. By dynamically correlating interaction patterns with content variations, the system optimizes educational delivery for diverse learners.
14. The system for correlating detected patterns with delivered content to improve the reception of the delivered content of claim 8 , wherein the content is an assessment and the different content directs the user to respond, using the user device, to the assessment.
This system operates in the domain of content delivery and user interaction analysis, specifically addressing the challenge of improving the effectiveness of assessments or other interactive content delivered to users. The system detects patterns in user behavior or responses and correlates these patterns with the content being delivered. By analyzing these correlations, the system can dynamically adjust or direct the content to enhance user engagement or accuracy of responses. The content in question is an assessment, such as a quiz or survey, which prompts the user to respond via their device. The system may present different versions of the assessment or follow-up content based on the detected patterns, ensuring the user is guided toward more effective or accurate responses. This adaptive approach helps tailor the assessment experience to individual users, improving the quality and reliability of the collected data. The system may also track how users interact with the assessment, such as response times or answer choices, to refine future content delivery. The goal is to optimize the assessment process by leveraging real-time user behavior data to enhance the relevance and impact of the delivered content.
15. A system for detecting multiple patterns during content delivery to improve the reception of delivered content, the system comprising: a network; a first user device, connected to the network, including a first image sensor, wherein the first user device is authenticated to a first user; a second user device, connected to the network, including a second image sensor, wherein the second user device is authenticated to a second user; a pattern engine connected to the network that: delivers a content to the first user device, delivers the content to the second user device, receives a first pattern, wherein the first pattern is a function of a first user facial expression captured by the first image sensor on the first user device and the first pattern is aligned, in time, with the content; receives a second pattern, wherein the second pattern intersects with the first pattern, and wherein the second pattern is a function of the second user facial expression captured by the second image sensor on the second user device and the second pattern is aligned, in time, with the content; retrieves: a plurality of generic patterns linked to a plurality of generic values from a pattern store connected to the network, wherein the plurality of generic patterns are digitally captured, and/or: a plurality of first user patterns linked to a plurality of first user values from a first user profile data store connected to the network, wherein the plurality of first user patterns are digitally captured and linked to the first user, and compares the first pattern with the plurality of generic patterns and/or the plurality of first user patterns to identify one of the plurality of generic patterns and/or the plurality of first user patterns that matches the first pattern; determines a first value from a generic value and/or a first user value linked to the one of the plurality of generic patterns and/or the plurality of first user patterns that matches the first pattern as a result of the comparison; links the first pattern with the first value; retrieves: a plurality of generic patterns linked to a plurality of generic values from a pattern store connected to the network, wherein the plurality of generic patterns have been digitally captured, and/or: a plurality of second user patterns linked to a plurality of second user values from a second user profile data store, connected to the network, wherein the plurality of second user patterns are digitally captured and linked to the second user; compares the second pattern with the generic patterns and/or the plurality of second user patterns to identify one of the plurality of generic patterns and/or the plurality of second user patterns that matches the second pattern; determines a second value from a generic value and/or a first user value linked to the one of the plurality of generic patterns and/or the plurality of second user patterns that matches the second pattern as a result of the comparison; links the second pattern to the second value; and a data server that: adds the first pattern, linked to the first pattern, value to the first user profile data store; and adds the second pattern, linked to the second pattern, value to the second user profile data store; and a content manager connected to the network that: receives the first pattern value, receives the second pattern value, combines the first pattern value and the second pattern value to form a combined pattern value, determines a workflow from a plurality of workflows identified by the combined pattern value, initiates the workflow, wherein one of the plurality of workflows includes sending an alert to a supervisor device, and sends the alert to the supervisor device.
This system detects and analyzes facial expression patterns from multiple users during content delivery to improve content reception. The system includes a network-connected pattern engine that delivers content to authenticated user devices equipped with image sensors. The pattern engine captures and aligns facial expression patterns from multiple users in real time with the delivered content. These patterns are compared against stored generic patterns and user-specific patterns from respective data stores. The system retrieves linked values (e.g., emotional responses, engagement levels) for matching patterns and associates these values with the captured patterns. The data is stored in user profiles. A content manager then combines the pattern values from different users to form a combined pattern value, which determines a workflow. Workflows may include sending alerts to supervisors or adjusting content delivery based on collective user responses. The system enables real-time analysis of multi-user reactions to content, enhancing personalized and adaptive content delivery.
16. The system for detecting multiple patterns during content delivery to improve the reception of delivered content of claim 15 , wherein the content includes a music content, a video content, a game content, or an advertising content.
This system detects multiple patterns during content delivery to enhance the reception of delivered content, such as music, video, game, or advertising content. The system analyzes the content in real-time to identify patterns, such as user engagement metrics, content structure, or delivery performance, and adjusts the delivery process accordingly. For example, it may modify playback speed, adjust compression levels, or optimize network routing based on detected patterns to improve user experience. The system also monitors feedback from recipients, such as interaction rates or error reports, to refine pattern detection and delivery strategies. By dynamically adapting to identified patterns, the system ensures that content is delivered in a way that maximizes reception quality and user satisfaction. The system may operate across various types of content, including audio, video, interactive media, and advertisements, ensuring consistent performance across different delivery scenarios. The underlying technology involves machine learning or statistical analysis to recognize patterns and apply corrective actions automatically, reducing the need for manual intervention. This approach improves content delivery efficiency and reliability, particularly in environments with variable network conditions or diverse user preferences.
17. The system for detecting multiple patterns during content delivery to improve the reception of delivered content of claim 15 , wherein the alert instructs the supervisor using the supervisor device to change from delivering a first content to delivering a second content.
A system detects multiple patterns during content delivery to improve reception of the delivered content. The system monitors content delivery to identify patterns in user engagement, such as attention levels, interaction rates, or feedback signals. When a pattern indicates poor reception, the system generates an alert to a supervisor device. The supervisor, upon receiving the alert, can adjust the content delivery in real-time. Specifically, the alert instructs the supervisor to switch from delivering a first content to a second content, optimizing engagement and improving reception. The system may analyze various data sources, such as user behavior metrics, environmental factors, or device performance, to determine the most effective content adjustments. By dynamically responding to detected patterns, the system enhances the overall quality and effectiveness of content delivery.
18. The system for detecting multiple patterns during content delivery to improve the reception of delivered content of claim 15 , wherein the alert instructs the supervisor using the supervisor device to pause content delivery for a specified amount of time.
A system detects multiple patterns during content delivery to improve reception quality. The system monitors content delivery in real-time, identifying patterns such as signal degradation, user engagement drops, or technical errors. When a problematic pattern is detected, the system generates an alert to a supervisor device. The alert includes instructions for the supervisor to pause content delivery for a specified duration, allowing time to address the issue before resuming. The system may also analyze historical data to predict potential disruptions and preemptively adjust delivery parameters. The supervisor device provides a user interface for the supervisor to review alerts, view detailed pattern data, and manually override automated responses if necessary. The system integrates with content delivery networks, streaming platforms, or broadcast systems to ensure seamless adjustments. By dynamically responding to detected patterns, the system enhances content reception quality, reduces interruptions, and improves user experience. The system may also log corrective actions for future reference and optimization.
19. The system for detecting multiple patterns during content delivery to improve the reception of delivered content of claim 15 , wherein the alert instructs the supervisor device to request the supervisor to ask the first user and/or the second user a question.
A system detects multiple patterns during content delivery to improve reception of the delivered content. The system monitors interactions between users and content, identifying patterns such as engagement levels, comprehension, or behavioral responses. When specific patterns are detected, the system generates an alert to a supervisor device. The alert instructs the supervisor to ask one or more users a question, facilitating real-time feedback or intervention. The supervisor device may be a computing device operated by a supervisor, such as a teacher, trainer, or moderator, who oversees the content delivery process. The system enhances content reception by dynamically adjusting interactions based on detected patterns, ensuring users remain engaged and understand the material. The question posed by the supervisor may relate to the content, user experience, or other relevant factors, helping to clarify misunderstandings or reinforce learning. This approach improves the effectiveness of content delivery by incorporating real-time user feedback and adaptive supervision.
20. The system for detecting multiple patterns during content delivery to improve the reception of delivered content of claim 15 , wherein the alert instructs the supervisor using the supervisor device to change the content delivery method.
The system detects multiple patterns during content delivery to improve reception quality. It monitors content transmission in real-time, identifying recurring issues such as signal degradation, latency spikes, or error rates that may affect user experience. The system analyzes these patterns to determine their impact on content delivery performance and generates alerts when critical thresholds are exceeded. These alerts are sent to a supervisor device, providing detailed instructions to adjust the content delivery method. The supervisor can then modify parameters such as transmission protocols, bandwidth allocation, or routing paths to mitigate the detected issues. The system may also log historical data for trend analysis, enabling proactive adjustments to prevent future disruptions. By dynamically responding to detected patterns, the system ensures consistent and high-quality content delivery, reducing downtime and enhancing user satisfaction. The supervisor device may include interfaces for real-time monitoring, alert management, and configuration changes, allowing for quick decision-making and system optimization.
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February 18, 2020
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